TL;DR: In this article, it was shown that a computer can learn to play a better game of checkers than can be played by the person who wrote the program, in a remarkably short period of time (8 or 10 hours of machine-playing time) when given only the rules of the game, a sense of direction, and a redundant and incomplete list of parameters which are thought to have something to do with the game.
Abstract: Two machine-learning procedures have been investigated in some detail using the game of checkers. Enough work has been done by verify the fact that a computer can be programmed so that it will learn to play a better game of checkers than can be played by the person who wrote the program. Furthermore, it can learn to do this in a remarkably short period of time (8 or 10 hours of machine-playing time) when given only the rules of the game, a sense of direction, and a redundant and incomplete list of parameters which are thought to have something to do with the game, but whose correct signs and relative weights are unknown and unspecified. The principles of machine learning verified by these experiments are, of course, applicable to many other situations.
TL;DR: Assessment of the effects of motivationally relevant conditions and individual differences on emotional experience and performance on a learning task found that children in the controlling condition experienced more pressure and evidenced a greater deterioration in rote learning over an 8-(+/- 1) day follow-up.
Abstract: Ninety-one fifth-grade children participated in a study that assessed the effects of motivationally relevant conditions and individual differences on emotional experience and performance on a learning task. Two directed-learning conditions, one controlling and one noncontrolling, were contrasted with each other and with a third nondirected, spontaneous-learning context. Both directed sets resulted in greater rote learning compared with the nondirected-learning condition. However, both the nondirected and the noncontrolling directed-learning sets resulted in greater interest and conceptual learning compared with the controlling set, presumably because they were more conducive to autonomy or an internal perceived locus of causality. Furthermore, children in the controlling condition experienced more pressure and evidenced a greater deterioration in rote learning over an 8-(+/- 1) day follow-up. Individual differences in children's autonomy for school-related activities as measured by the Self-Regulation Questionnaire (Connell & Ryan, 1985) also related to outcomes, with more self-determined styles predicting greater conceptual learning. Results are discussed in terms of the role of autonomy in learning and development and the issue of directed versus nondirected learning.
TL;DR: An Introduction to Strategies and Styles of Learning RR Schmeck Motivational Factors in Students' Approaches to Learning N Entwistle Describing and Improving Learning F Marton Learning Strategies, Teaching Strategies, and Conceptual or Learning Style G Pask Simultaneous-Successive Processing and Planning JP Das Students' Self-Concepts and the Quality of Learning in Public Schools and Universities P McCarthy, RR SchMEck Applications of the Concepts of Strategy and Style: Context and Strategy: Situational Influences on Learning P Ramsden Approaches To Learning and Essay Writing
Abstract: An Introduction to Strategies and Styles of Learning RR Schmeck Motivational Factors in Students' Approaches to Learning N Entwistle Describing and Improving Learning F Marton Learning Strategies, Teaching Strategies, and Conceptual or Learning Style G Pask Simultaneous-Successive Processing and Planning JP Das Students' Self-Concepts and the Quality of Learning in Public Schools and Universities P McCarthy, RR Schmeck Applications of the Concepts of Strategy and Style: Context and Strategy: Situational Influences on Learning P Ramsden Approaches to Learning and Essay Writing J Biggs Style, Strategy, and Skill in Reading J Kirby Styles of Thinking and Creativity P Torrance, Z Rockenstein Assessment and Training of Student Learning Strategies C Weinstein Strategies and Styles of Learning: An Integration of Varied Perspectives RR Schmeck Index
TL;DR: In this paper, Rote versus meaningful learning is discussed in the context of Bloom's taxonomy and its application in theory-into-practice (T2P) setting.
Abstract: (2002). Rote Versus Meaningful Learning. Theory Into Practice: Vol. 41, Revising Bloom's Taxonomy, pp. 226-232.